In: Statistics and Probability
5) In the OmniPower Bars scenario, your business objective, to determine the effect that price and in-store promotional expenses will have on sales, calls for examining a multiple regression model in which the price of an OmniPower Bar in cents (X1) and the monthly budget for in-store promotional expenses in dollars (X2) are the independent variables and the number of OmniPower Bars sold in a month (Y) is the dependent variable. The data has been collected from a sample of 34 stores in a supermarket chain selected for a test-market study of OmniPower. The data is organized and stored in OmniPower.xlsx file.
(a) State the multiple regression equation.
(b) Interpret the meaning of 1 and 2, in this problem. Significance/Meaning of 1: ____________________________________________________ Significance/Meaning of 2: ____________________________________________________
(c) What is the significance of 0? Significance/Meaning of 0: ____________________________________________________
(d) Predict the mean sales for a store charging $0.69 during a month in which promotion expenses are $300.
(a) The multiple regression equation is:
Y = 5,837.5208 -53.2173*X1 + 3.6131*X2
(b) For every addition in the price of an OmniPower Bar in cents, the number of OmniPower Bars sold in a month will decrease by 53.2173.
For every additional monthly budget for in-store promotional expenses in dollars, the number of OmniPower Bars sold in a month will increase by 3.6131.
(c) There is no meaning of y-intercept because the independent variables cannot be constant.
(d) Y = 5,837.5208 -53.2173*0.69 + 3.6131*300 = 6884.72
R² | 0.758 | |||||
Adjusted R² | 0.742 | |||||
R | 0.870 | |||||
Std. Error | 638.065 | |||||
n | 34 | |||||
k | 2 | |||||
Dep. Var. | Sales | |||||
ANOVA table | ||||||
Source | SS | df | MS | F | p-value | |
Regression | 3,94,72,730.7730 | 2 | 1,97,36,365.3865 | 48.48 | 2.86E-10 | |
Residual | 1,26,20,946.6682 | 31 | 4,07,127.3119 | |||
Total | 5,20,93,677.4412 | 33 | ||||
Regression output | confidence interval | |||||
variables | coefficients | std. error | t (df=31) | p-value | 95% lower | 95% upper |
Intercept | 5,837.5208 | |||||
Price | -53.2173 | 6.8522 | -7.766 | 9.20E-09 | -67.1925 | -39.2421 |
Promotion | 3.6131 | 0.6852 | 5.273 | 9.82E-06 | 2.2155 | 5.0106 |